Change detection schemes are known in the art for applications such as security applications. A change occurring in a video image can mean that an intruder is entering, for example. By only monitoring changes in images, storage requirements can be reduced, particularly if digital images are being recorded. There is no point using storage to save multiple copies of background visual information that does not change. Change detection is also useful in medical and other applications.
Change detection techniques typically rely on clustering schemes that identify the coordinates of pixels that have changed between different time intervals. Change detection metrics generally operate by detecting numerical differences in corresponding pixel values between the different time intervals.
Photographs taken over time capture changes of the captured objects. The changes may be obvious to an observing viewer or they may be inconspicuous even to a keen observer. If the changes are subtle, such as for example, blood vessel damage during eye surgery, such changes may not readily show up in a side-by-side comparison of two photographs taken at different instances in time.
Accordingly, a system and method are required to expose inconspicuous differences from a plurality of photographs that are taken at different instances in time.